---
title: "R可视乎"
author: "庄闪闪"
output:
flexdashboard::flex_dashboard:
orientation: rows
social: menu
source_code: embed
---
```{r setup, include=FALSE}
library(ggplot2)
library(plotly)
library(plyr)
library(flexdashboard)
# Make some noisily increasing data
set.seed(955)
dat <- data.frame(cond = rep(c("A", "B"), each=10),
xvar = 1:20 + rnorm(20,sd=3),
yvar = 1:20 + rnorm(20,sd=3))
```
散点图
=======================================================================
Row
-----------------------------------------------------------------------
### Scatter Chart with geom_point
```{r}
p <- ggplot(dat, aes(x=xvar, y=yvar)) +
geom_point(shape=1) # Use hollow circles
ggplotly(p)
```
### geom_smooth Linear Regression
```{r}
p <- ggplot(dat, aes(x=xvar, y=yvar)) +
geom_point(shape=1) + # Use hollow circles
geom_smooth(method=lm) # Add linear regression line
ggplotly(p)
```
Row
-----------------------------------------------------------------------
### geom_smooth with Loess Smoothed Fit
```{r}
p <- ggplot(dat, aes(x=xvar, y=yvar)) +
geom_point(shape=1) + # Use hollow circles
geom_smooth() # Add a loess smoothed fit curve with confidence region
ggplotly(p)
```
### Constraining Slope with stat_smooth
```{r}
n <- 20
x1 <- rnorm(n); x2 <- rnorm(n)
y1 <- 2 * x1 + rnorm(n)
y2 <- 3 * x2 + (2 + rnorm(n))
A <- as.factor(rep(c(1, 2), each = n))
df <- data.frame(x = c(x1, x2), y = c(y1, y2), A = A)
fm <- lm(y ~ x + A, data = df)
p <- ggplot(data = cbind(df, pred = predict(fm)), aes(x = x, y = y, color = A))
p <- p + geom_point() + geom_line(aes(y = pred))
ggplotly(p)
```